Relevant bibliographies by topics / Trading volume

Academic literature on the topic 'Trading volume'

Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

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Journal articles on the topic "Trading volume"

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Bornholt, Graham, Paul Dou, and Mirela Malin. "Trading Volume and Momentum: The International Evidence." Multinational Finance Journal 19, no. 4 (December 1, 2015): 267–313. http://dx.doi.org/10.17578/19-4-2.

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Guasoni, Paolo, and Marko Weber. "DYNAMIC TRADING VOLUME." Mathematical Finance 27, no. 2 (June 19, 2015): 313–49. http://dx.doi.org/10.1111/mafi.12099.

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McSherry, Bernard, and Berry K. Wilson. "Deflation and Reflation: The Pre-WW I Impact on NYSE Trading Volumes and Seat Prices." Journal of Economics and Public Finance 2, no. 1 (March 29, 2016): 106. http://dx.doi.org/10.22158/jepf.v2n1p106.

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<em>The study analyzes a unique time period of sustained deflation from 1867 to 1896, followed by sustained reflation after 1896. We use these periods to test two hypotheses concerning the impact on NYSE trading volumes and seat prices. The first is the “liquidity-trading” hypothesis, which hypothesizes that liquidity trading, a component of total trading volume, is positively correlated with interest rates. The second is the price-volume relationship, which hypothesizes a positive relationship between stock prices returns and changes in trading volume. These hypotheses suggest that NYSE trading volume should fall (rise) with falling (rising) stock prices and interest rates. We find strong support for both hypotheses, and additionally show that the impact of stock market prices on trading volumes is highly asymmetrical. As well, the study argues and finds evidence that the high level of systematic risk found in the pricing of NYSE seats is another reflection of the price-volume relationship. Therefore, the study finds strong evidence of a link between deflation, reflation and market liquidity as reflected in trading volumes and the pricing of NYSE seats.</em>
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Mudalige, Priyantha, Petko S. Kalev, and Huu Nhan Duong. "Individual and institutional trading volume around firm-specific announcements." International Journal of Managerial Finance 12, no. 4 (August 1, 2016): 422–44. http://dx.doi.org/10.1108/ijmf-01-2016-0007.

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Purpose – The purpose of this paper is to investigate the immediate impact of firm-specific announcements on the trading volume of individual and institutional investors on the Australian Securities Exchange (ASX), during a period when the market becomes fragmented. Design/methodology/approach – This study uses intraday trading volume data in five-minute intervals prior to and after firm-specific announcements to measure individual and institutional abnormal volume. There are 70 such intervals per trading day and 254 trading days in the sample period. The first 10 minutes of trading (from 10.00 to 10.10 a.m.) is excluded to avoid the effect of opening auction and to ensure consistency in the “starting time” for all stocks. The volume transacted during five-minute intervals is aggregated and attributed to individual or institutional investors using Broker IDs. Findings – Institutional investors exhibit abnormal trading volume before and after announcements. However, individual investors indicate abnormal trading volume only after announcements. Consistent with outcomes expected from a dividend washing strategy, abnormal trading volume around dividend announcements is statistically insignificant. Both individual and institutional investors’ buy volumes are higher than sell volumes before and after scheduled and unscheduled announcements. Research limitations/implications – The study is Australian focused, but the results are applicable to other limit order book markets of similar design. Practical implications – The results add to the understanding of individual and institutional investors’ trading behaviour around firm-specific announcements in a securities market with continuous disclosure. Social implications – The results add to the understanding of individual and institutional investors’ trading behaviour around firm-specific announcements in a securities market with continuous disclosure. Originality/value – These results will help regulators to design markets that are less predatory on individual investors.
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de Beer, Johan. "The price and volume effect of initial single stock futures trading." Corporate Ownership and Control 7, no. 2 (2009): 367–86. http://dx.doi.org/10.22495/cocv7i2c3p4.

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The introduction of single stock futures to a market allows for a per company impact-assessment of futures trading activity. Thirty-eight South African companies were evaluated in terms of a possible price and volume effect due to the initial trading of their respective single stock futures contracts. An event study revealed that SSF trading had little impact on the underlying share prices while a normalised volume comparison pre to post SSF trading showed a general increase in spot market trading volumes.
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Pak, Dohyun, and Sun-Yong Choi. "Economic Policy Uncertainty and Sectoral Trading Volume in the U.S. Stock Market: Evidence from the COVID-19 Crisis." Complexity 2022 (April 25, 2022): 1–15. http://dx.doi.org/10.1155/2022/2248731.

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We empirically analyze the impact of economic uncertainty due to the COVID-19 pandemic on the trading volume of each sector in the S&P 500 index. Wavelet coherence analysis is carried out using economic policy uncertainty data and the trading volume of each sector in the S&P 500 index from July 2004 to September 2020. Furthermore, we apply multifractal detrended fluctuation (MF-DFA) analysis to the trading volume series of all sectors. The wavelet coherence analysis shows that the COVID-19 pandemic has substantially influenced trading volume in all sectors. However, the impact of the pandemic is different from that during the global financial crisis in some sectors, such as information technology, consumer discretionary, and communication services. Because of the lockdown taken to suppress COVID-19, increased remote working and remote learning are the main reasons for these results. Additionally, according to the MF-DFA analysis, the trading volume of all the sectors has clear multifractal characteristics, and they are all nonpersistent. Specifically, trading volumes of the real estate and materials sector are highly correlated, whereas the trading volumes of industry and information technology sectors are comparatively less correlated.
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Mpofu, Raphael Tabani. "The relationship between trading volume and stock returns in the JSE securities exchange in South Africa." Corporate Ownership and Control 9, no. 4-2 (2012): 199–207. http://dx.doi.org/10.22495/cocv9i4c2art1.

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This study examines the relationship between trading volume and stock returns in the JSE Securities Exchange in South Africa. The study looked at the price and trading returns of the FTSE/JSE index from July 22, 1988 till June 11, 2012. The study revealed that stock returns are positively related to the contemporary change in trading volume. Further, it was found that past returns were not affected significantly by changes in trading volumes. The results present a significant relationship between trading volume and the absolute value of price changes. Autoregressive tests were used to explore whether return causes volume or volume causes return. The results suggest that volume is influenced by a lagged returns effect for the FTSE/JSE index. Therefore, return seems to contribute some information to investors when they make investment decisions.
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Kim, Taejin. "Trust and trading volume." Economics Letters 207 (October 2021): 110003. http://dx.doi.org/10.1016/j.econlet.2021.110003.

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Glaser, Markus, and Martin Weber. "Overconfidence and trading volume." Geneva Risk and Insurance Review 32, no. 1 (June 2007): 1–36. http://dx.doi.org/10.1007/s10713-007-0003-3.

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Dewi, Catur Kumala. "JKSE AND TRADING ACTIVITIES BEFORE AFTER COVID-19 OUTBREAK." Research Journal of Accounting and Business Management 4, no. 1 (June 6, 2020): 1. http://dx.doi.org/10.31293/rjabm.v4i1.4671.

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The Covid-19 outbreak gave a negative implication not only on the Indonesian stock exchange but throughout the world until WHO declared Covid-19 a pandemic. Stock market movements are formed by stock market participants, including issuers, brokers and investors. IHSG continues to fluctuate sharply and tends to decrease in the beginning of January 2020 to April 2020. Different things happen for trading volumes that have increased. Trading volume is a combination of sell and buy during the trading session. Before and after Covid-19, IHSG gives an illustration that trading volume is increasingly fluctuating sharply with an upward trend above trading volume before Covid-19. Pandemic provides an overview of IHSG volatility and trading volumes that experience sharp fluctuations with a downward trend. Therefore, reserves are better if diversification is carried out in real assets other than financial assets.
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Dissertations / Theses on the topic "Trading volume"

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Knutsson, Greta, and Kamyar Espahbodi. "Trading volume at Avanza." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254226.

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Producing a model explaining the trading volume can be attractive for companies who’s main revenue resides on it. Previous studies have shown that factors such as stock returns, volatility and uncertainty affects the trading volume. The purpose of this work is to clarify the consensus that prevails and determine the factors that impact Avanza’s customers trading volume. Factors such as daily stock returns and economic, political and financial uncertainty are analyzed through a multiple linear regression analysis with a daily time period between 2000-2019. The work is thus designed within the framework of mathematical statistics and industrial economics. To be able to draw a conclusion, further investigation is required in the form of a time series analysis in combination with a deeper understanding of the applied area and the mathematical methods that have been used.
Att ta fram en modell som förklarar handelsvolymen kan vara eftertraktat hos företag vars huvudintäkter beror av den. Tidigare forskning visar att faktorer som prisförändringar på aktiemarknaden, volatilitet och osäkerhet påverkar handelsvolymen. Syftet med arbetet är att klargöra den konsensus som råder och fastställa de faktorer som har störst påverkan gällande handelsvolymen för Avanza’s kunders. Faktorer som dagliga förändringar inom börsmarknaden och ekonomisk, politisk och finansiell osäkerhet har genom en multipel linjär regressionsanalys analyserats med en daglig tidsperiod mellan 2000-2019. Arbetet är således utformat inom ramen för matematisk statistik och industriell ekonomi. För att kunna dra en slutsats krävs vidare undersökning i form av en tidsserieanalys och en djupare förståelse av det tillämpade området och metoderna som har an- vänds.
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MA, GUOHUA. "THREE ESSAYS ON TRADING VOLUME." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1179254828.

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Wavasseur, Maxime. "Asset Pricing and Trading Volume." Thesis, Toulouse 1, 2018. http://www.theses.fr/2018TOU10069/document.

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Ce mémoire de thèse est organisé en trois articles. Le premier est dédié au cas des moulins de Toulouse dont les données nous permettent de tester certains points de la théorie de l’évaluation des actifs. Plus précisément, nous proposons une mesure de la consommation locale et réalisons une analyse basée sur l’entropie relative pour extraire le facteur stochastique d’actualisation de cette économie. Nous observons que ce dernier est lié à la consommation et qu’un modèle simple à la Lucas n’est pas rejeté pour des niveaux d’aversion pour le risque bas. Dans le second article, nous décrivons de manière purement théorique la relation entre le volume d’échange et la composition du marché par le biais d’un modèle où les préférences d’un agent dépendent de son environnement et où un choc de liquidité peut survenir de manière collective pour tous les membres d’un même groupe. Nous introduisons alors le concept de canal désirable comme condition nécessaire à la réalisation d’un échange et lions la topologie du réseau au volume espéré des échanges. Le troisième article porte sur le rôle des statuts sociaux dans la dynamique de marché. Nous proposons un modèle où deux types de biens sont disponibles, un bien positionnel et un bien non positionnel. En distinguant dans l’économie ceux possédant un statut et ceux qui n’en possèdent pas nous justifions comment les échanges prennent place au cours du temps par rapport à cette distinction sociale. Les prédictions du modèle sont alors testées sur les données historiques des moulins de Toulouse
This doctoral thesis is organized in three articles. In the first one, we use the Toulouse mills companies data as a suitable testbed for asset pricing theory. More precisely, we provide a proxy for local consumption and perform a relative entropy analysis to extract the stochastic discount factor of this old economy. We found that the model-free pricing kernel correlates with consumption and a standard CRRA-model is not rejected by the data, even for very low risk aversion levels. In the second article, we describe the relationship between trading volume and market composition through a pure theoretical approach. We build a model where the agent preferences depend on his environment and a liquidity shock is collectively experienced by the members of each social group in the economy. We introduce the concept of desirability channel as a necessary condition for a trade to occur and we rely the topology of the network to the expected volume. The third article focus on the role of social status concern in the exchanges dynamic. We propose a setting where two types of goods are available, a positional and a non positional one. By splitting the economy into two social groups, we depict how trades take place over time regarding to these social groups. The model predictions are finally tested on the historical support of the Toulouse mills companies
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Johansson, Henrik, and Niklas Wilandh. "Trading volume : The behavior in information asymmetries." Thesis, Jönköping University, JIBS, Business Administration, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-238.

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According to theory, trading volume decreases in information asymmetries, i.e. when there are differences in information. This is due to the fact that uninformed investors delay their trades when they are facing adverse selection. When the asymmetry is resolved there should be a corresponding increase in trading volume. Around earnings announcements (scheduled an-nouncements) this asymmetry is greater than normal, hence one can expect a decrease in trading volume. Around unexpected announcements such as acquisition announcement (unscheduled announcements) a total increase is instead expected because of an increase in trading by informed investors. All these effects are likely to be greater for smaller stocks.

The purpose of this thesis is to investigate the trading volume before- and after scheduled announcements and the trading volume before unscheduled announcements in order to investigate how informed- and uninformed investors behave in information asymmetries on Stockholmsbörsen.

The method is quantitative with secondary data from the Stockholm Stock exchange from 1998-2004. The method is the same as Chae (2005) uses with paired-samples t-tests. It tests whether the change in trading volume is different from a benchmark consisting of an average of the trading volume 30 days before the announcement.

We found a statistically significant decrease in trading volume in 6 of 10 days before a scheduled announcement and an increase also on 7 of 10 days after the announcement. For unscheduled announcements we found an increase before it was released but were not able to prove it statistically. We conclude that uninformed investors behave strategically before scheduled announcements in order to avoid adverse selection. We could not conclude that the effects are greater for smaller stocks.

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Basu, Somnath. "Information, expectations and equilibrium: Trading volume hypotheses." Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/185109.

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In analyses of the relationship between information and price-volume reactions, the role of investor expectations is often considered implicitly. Not allowing investors to either disagree among each other or remain uninformed is a consequence of the assumption of a free and perfect information flow. A more flexible definition of information allows the observation that trading volume is an accurate reflector of investor expectations and contains valuable information about price movements. Trading volume is also used to empirically show the effects of imperfect information and the inappropriateness of the event study method.
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Wang, Hanfeng. "Essays on stock trading volume, volatility and information." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/hkuto/record/B38826185.

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Wang, Hanfeng, and 王漢鋒. "Essays on stock trading volume, volatility and information." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38826185.

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Rougier, Jonathan. "Price change and trading volume in a speculative market." Thesis, Durham University, 1996. http://etheses.dur.ac.uk/5347/.

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This thesis is concerned with the daily dynamics of price change and trading volume in a speculative market. The first part examines the news-driven model of Tauchen and Pitts (1983), and develops this model to the point where it is directly testable. In order to implement the test a new method for creating a price index from futures contracts is proposed. It is found that news effects can explain some but not all of the structure of the daily price/volume relationship. An alternative explanation is presented, in which the model of Tauchen and Pitts is generalized in a non-linear fashion. In the second part of the thesis, the presence of a small amount of positive autocorrelation in daily returns is exploited through the development of a timing rule. This timing rule applies to investors who are committed to a purchase but flexible about the precise timing. The computation of the timing rule is discussed in detail. In practice it is found that this timing rule is unlikely to generate sufficiently large returns to be of interest to investors in a typical stock market, supporting the hypothesis of market efficiency. However, the incorporation of extra information regarding price/volume dynamics, as suggested by the analysis of Part I, might lead to a much improved rule.
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Chiu, Shuk-man, and 趙淑文. "Trading volume in the housing market around land auctions events." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hdl.handle.net/10722/194612.

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Land and housing markets are separated, with the traders in the land market being developers and those in the housing market being end-users for self-occupation and investors for investment. The two markets, however, are closely related because demand for residential sites is derived from demand for housing. With this close relationship, any signals from the land market should be impounded to the housing market. Land auction, which is the most commonly adopted land disposal method in Hong Kong, is a significant event in the land market. The land auction events should contain market signals affecting trading decisions of homebuyers and sellers in the housing market in a similar way that corporate earnings announcements of a listed company affect the trading of its shares in the stock market. 　　This study investigates how land auctions affect trading volume in the secondary housing market in Hong Kong. Hypotheses are developed based on previous studies on the impacts of corporate earnings announcements on trading volume in stock markets with modifications to take into account the differences between housing and stock markets. The characteristics of housing market that are important in formulating the hypotheses are high transaction cost and market incompleteness (e.g. absence of short selling). In addition, lumpiness and indivisibility of housing, which make market participants risk-averse, also play important roles in the development of the hypotheses in this study. 　　The research results indicate that greater dispersion in prior beliefs before the land auctions is associated with lower trading volume in the housing spot market. Unexpected land auction outcomes, be they positive or negative, are also negatively related to trading volume in the housing market, with the negative outcomes exerting a strong downward pressure on trading volume. These findings are contradictory to the findings commonly found in most finance literature about trading volume around corporate earnings announcements which assumes negligible transaction cost but consistent with findings in Barron and Karpoff (2004). The deviation from previous studies of stock market can be explained by the risk-averse behaviour of market participants, high transaction cost and market incompleteness in the housing market. Although empirical data in Hong Kong are used, the implications are general and should be applicable to other housing markets with similar characteristics. This study also sheds light on how increase in transaction cost and restriction on short selling may affect trading volume around corporate earnings announcements in the stock market.
published_or_final_version
Real Estate and Construction
Doctoral
Doctor of Philosophy
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Rebelo, Paulo Tomaz. "Price moving average and volume." Master's thesis, Instituto Superior de Economia e Gestão, 2012. http://hdl.handle.net/10400.5/10394.

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Mestrado em Finanças
Este trabalho pretende testar uma das mais simples e populares ferramentas de análise técnica, as médias móveis, e a sua relação com o volume e as rendibilidades utilizando dados do índice PSI 20 desde 1992 até 2012. Os resultados sobre as rendibilidades suportam a eficácia da utilização desta estratégia mostrando que são estatisticamente superiores às da estratégia buy-and-hold, e ainda, que sinais de compra geram rendibilidades consistentemente superiores às que se seguem aos sinais de venda. Em suma, os resultados mostram que podem ser obtidas rendibilidades adicionais através de estratégias baseadas nas médias móveis sobre os preços. Este estudo tenta ainda investigar a relação entre volume e as rendibilidades diárias no mercado acionista português. Os resultados da regressão mostram que tanto os sinais de compra ou venda da estratégia de médias móveis como o volume têm pouco poder explicativo sobre as rendibilidades das ações. Esta conclusão parece não ser consistente com os resultados da análise sobre as rendibilidades.
This work tests one of the simplest and most popular trading rules, moving average, and the relationship with trading volume by utilizing the PSI 20 Index from 1992 to 2012. In the returns scope, our results provide strong support for this technical strategy. The returns obtained from this strategy are statistically higher than the simple buy-and-hold policy, and further, buy signals consistently generate higher returns than sell signals. Overall, our results show that additional returns can be obtained from a trading strategy based on this technical rule. This study also attempts to investigate the relationship between trading volume and daily stock returns. The results obtained from the regression show that both moving average signals and volume have little explanatory power on returns in the Portuguese stock market. This conclusion brings shy support to the trading efficacy that resulted from the returns analysis.
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Books on the topic "Trading volume"

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Trading on volume. New York: McGraw-Hill, 2002.

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Kim, Young Sam. The sensitivity of observed trading volume reactions to the choice of trading volume reaction metric. [Urbana, Ill.]: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1991.

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Lamont, Owen A. The earnings announcement premium and trading volume. Cambridge, Mass: National Bureau of Economic Research, 2007.

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Lamont, Owen. The earnings announcement premium and trading volume. Cambridge, MA: National Bureau of Economic Research, 2007.

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Fund, International Monetary, ed. Noise trading, transaction costs, and the relationship of stock returns and trading volume. Washington, D.C: International Monetary Fund, 1994.

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Willain, Pascal. Value in time: Better trading through effective volume. Hoboken, N.J: Wiley, 2008.

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Campbell, John Y. Trading volume and serial correlation in stock returns. Cambridge, MA: National Bureau of Economic Research, 1992.

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Willain, Pascal. Value in time: Better trading through effective volume. Hoboken, N.J: John Wiley & Sons, 2008.

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Lo, Andrew W. Asset prices and trading volume under fixed transaction costs. Cambridge, MA: National Bureau of Economic Research, 2001.

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He, Hua. Differential information and dynamic behavior of stock trading volume. Cambridge, MA: National Bureau of Economic Research, 1995.

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Book chapters on the topic "Trading volume"

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Röman, Jan R. M. "Trading Financial Instruments." In Analytical Finance: Volume I, 1–20. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-34027-2_1.

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Gomber, Peter, Benjamin Clapham, Jens Lausen, and Sven Panz. "The MiFIR Trading Obligation: Impact on Trading Volume and Liquidity in Electronic Trading." In Lecture Notes in Business Information Processing, 3–26. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19037-8_1.

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Porras, Eva R. "Bubbles and Technical Trading." In Bubbles and Contagion in Financial Markets, Volume 1, 127–71. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/9781137358769_5.

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Howison, S., and D. Lamper. "Trading Volume in Models of Financial Derivatives." In Progress in Industrial Mathematics at ECMI 2000, 57–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04784-2_5.

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Kwak, Youngsik, Yunkyung Lee, Jaeweon Hong, Wanwoo Cho, Ho Jang, and Daehyun Park. "From Trading Volume to Trading Number-Based Pricing at Home Trading System on Korean Stock Market." In Communications in Computer and Information Science, 463–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22333-4_60.

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Kapusuzoglu, Ayhan, and Nildag Basak Ceylan. "Trading Volume, Volatility and GARCH Effects in Borsa Istanbul." In Contributions to Management Science, 333–47. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77622-4_17.

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Magklasi, Ioanna. "The impact of volume contracts on the trading parties." In The Rotterdam Rules and International Trade Law, 134–85. New York, NY : Routledge, 2018.: Routledge, 2018. http://dx.doi.org/10.4324/9781315115153-6.

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Brändle, Alexander. "Results: Trading Volume and the Cross-Sectional Variation of Stock Returns." In Volume Based Portfolio Strategies, 98–188. Wiesbaden: Gabler, 2010. http://dx.doi.org/10.1007/978-3-8349-8716-7_4.

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Yang, Ning, Yongwei Liu, Wentao Lv, Chuncheng Gao, Shiqiang Zheng, and Qian Zhang. "Application of microservices in power trading platforms." In Advances in Energy, Environment and Chemical Engineering Volume 1, 176–83. London: CRC Press, 2022. http://dx.doi.org/10.1201/9781003330165-25.

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Ahlbeck, Jutta, Ann-Catrin Östman, and Eija Stark. "Introduction: Encounters and Trading Practices." In Encounters and Practices of Petty Trade in Northern Europe, 1820–1960, 1–27. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98080-1_1.

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AbstractDuring the nineteenth century, the circulation and exchange of various goods increased considerably, which affected trade on global, regional, and local levels. This volume uncovers one important yet neglected form of emerging itinerant livelihoods—namely, ambulatory petty trade—and how it was practiced in Northern Europe during the period 1820–1960. Northern Europe includes here the Nordic countries (Finland, Sweden, Norway, and Denmark), the Arctic and Subarctic Europe, and northern Estonia. The introductory chapter presents central concepts, such as livelihoods, petty trade, social and cultural encounters, along with theoretical premises, such as situated practices and materiality that underlie the collection. With the period chosen, 1820–1960, the chapter points to continuities and changes when it comes to inequalities and various forms livelihoods in the Nordic region.
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Conference papers on the topic "Trading volume"

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Darolles, Serge, and Gaëlle Le Fol. "Trading Volume and Arbitrage." In 4th Annual International Conference on Accounting and Finance (AF 2014). Global Science & Technology Forum (GSTF), 2014. http://dx.doi.org/10.5176/2251-1997_af14.27.

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Liu, Xunzhe, Yihui Liu, and Siyuan Ma. "Liquidity, Stock Return and Trading Volume." In the 2017 International Conference. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3089871.3089903.

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Li, Ziqian, Caixia Wang, Xiaoning Ye, Wei Wang, and Shuang Hao. "China's Green Certificate Trading Mode Design and Trading Volume Evaluation Model Establishment." In 2019 Chinese Automation Congress (CAC). IEEE, 2019. http://dx.doi.org/10.1109/cac48633.2019.8996576.

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Takada, Hellinton H., and Julio M. Stern. "Intraday trading volume and non-negative matrix factorization." In TECHNOLOGIES AND MATERIALS FOR RENEWABLE ENERGY, ENVIRONMENT AND SUSTAINABILITY: TMREES. Author(s), 2016. http://dx.doi.org/10.1063/1.4959065.

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Souply, Marc, Marc Malmaison, Francois Rioult, and Bertrand Cuissart. "Sales Volume Prediction and Application to Materials Trading." In 2022 IEEE International Conference on Smart Computing (SMARTCOMP). IEEE, 2022. http://dx.doi.org/10.1109/smartcomp55677.2022.00054.

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Brooks, R., and E. Harris. "Price and volume relationships across water trading zones." In SUSTAINABLE IRRIGATION 2012. Southampton, UK: WIT Press, 2012. http://dx.doi.org/10.2495/si120381.

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Liu, Yucan, and Jing Xue. "Research on IPO Underpricing, Trading Volume and Investor Interest." In 2010 International Conference on Management and Service Science (MASS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icmss.2010.5578230.

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Doeksen, B., A. Abraham, J. Thomas, and M. Paprzycki. "Real stock trading using soft computing models." In International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II. IEEE, 2005. http://dx.doi.org/10.1109/itcc.2005.238.

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Wang, Shaosong, and Weihua Liu. "Weather Impacts on Trading Volume-Evidence from Hang Seng Index." In 2017 2nd International Seminar on Education Innovation and Economic Management (SEIEM 2017). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/seiem-17.2018.116.

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Ishihara, Y., Runhe Huang, and Jianhua Ma. "A Real Trading Model based Price Negotiation Agents." In 20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06). IEEE, 2006. http://dx.doi.org/10.1109/aina.2006.52.

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Reports on the topic "Trading volume"

1

Lamont, Owen, and Andrea Frazzini. The Earnings Announcement Premium and Trading Volume. Cambridge, MA: National Bureau of Economic Research, May 2007. http://dx.doi.org/10.3386/w13090.

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Campbell, John, Sanford Grossman, and Jiang Wang. Trading Volume and Serial Correlation in Stock Returns. Cambridge, MA: National Bureau of Economic Research, October 1992. http://dx.doi.org/10.3386/w4193.

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He, Hua, and Jiang Wang. Differential Information and Dynamic Behavior of Stock Trading Volume. Cambridge, MA: National Bureau of Economic Research, February 1995. http://dx.doi.org/10.3386/w5010.

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Lo, Andrew, Harry Mamaysky, and Jiang Wang. Asset Prices and Trading Volume Under Fixed Transactions Costs. Cambridge, MA: National Bureau of Economic Research, May 2001. http://dx.doi.org/10.3386/w8311.

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Lo, Andrew, and Jiang Wang. Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory. Cambridge, MA: National Bureau of Economic Research, March 2000. http://dx.doi.org/10.3386/w7625.

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Lo, Andrew, and Jiang Wang. Trading Volume: Implications of An Intertemporal Capital Asset Pricing Model. Cambridge, MA: National Bureau of Economic Research, October 2001. http://dx.doi.org/10.3386/w8565.

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Brock, William, and Blake LeBaron. A Dynamic Structural Model for Stock Return Volatility and Trading Volume. Cambridge, MA: National Bureau of Economic Research, January 1995. http://dx.doi.org/10.3386/w4988.

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Chen, Joseph, Harrison Hong, and Jeremy Stein. Forecasting Crashes: Trading Volume, Past Returns and Conditional Skewness in Stock Prices. Cambridge, MA: National Bureau of Economic Research, May 2000. http://dx.doi.org/10.3386/w7687.

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Stein, Jeremy. Prices and Trading Volume in the Housing Market: A Model with Downpayment Effects. Cambridge, MA: National Bureau of Economic Research, March 1993. http://dx.doi.org/10.3386/w4373.

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Helpman, Elhanan, Marc Melitz, and Yona Rubinstein. Estimating Trade Flows: Trading Partners and Trading Volumes. Cambridge, MA: National Bureau of Economic Research, February 2007. http://dx.doi.org/10.3386/w12927.

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